A real-world industrial benchmark and agentic baseline show current LLMs often fail to produce correct, stable, deployable visual workflows from natural language, with only modest resolve-rate gains.
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A 3B model with few-shot prompting reaches 79.7% of GPT-5 tool-use performance while a hypernetwork adaptation adds zero measurable benefit across four benchmarks.
Proposes autopoietic architectures for self-constructing software as a fundamental shift in the SDLC, leveraging foundation models for autonomous evolution and maintenance.
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Chat2Workflow: A Benchmark for Generating Executable Visual Workflows with Natural Language
A real-world industrial benchmark and agentic baseline show current LLMs often fail to produce correct, stable, deployable visual workflows from natural language, with only modest resolve-rate gains.
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Meta-Tool: Efficient Few-Shot Tool Adaptation for Small Language Models
A 3B model with few-shot prompting reaches 79.7% of GPT-5 tool-use performance while a hypernetwork adaptation adds zero measurable benefit across four benchmarks.
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